 365. Technology by itself cannot provide effective detection and response. Skilled experts are hard to find. Organizations lack threat intelligence that is applicable and actionable. At Herjavec Group, we are laser focused on protecting your data and your business. Information security is what we do. From the Walt Disney World Swan and Dolphin Resort in Orlando, Florida. It's the queue. Coveringsplunk.com 2016. Brought to you by Splunk. Now here are your hosts, John Furrier and John Walls. Hey, welcome back, everyone. We are live in Orlando, Florida with Splunk.com. This is the queue exclusive coverage. This is SiliconANGLE's flagship program, the queue where we go out to the events and extract the signal of noise. I'm John Furrier with my co-host this week, John Walls. Well, John, you talk about the noise. We have a lot of good noise here, which is there's a lot of signal and a lot of noise. We're joined by Shy Molem now, who's a VP of product marketing at Splunk. Shy, good to see you. Thanks for joining us here on the queue. We appreciate that. First off, I mean, we kind of kid about the noise, but there is a there's a good vibe here, right? I mean, very upbeat. A lot of positivity, if you will. I mean, what's your take on what's happening in your environment right now? We've got the best customers in the industry, guys. There is an electrifying energy. When we get our customers together, they're doing amazing things with Splunk. And you definitely feel that energy here today. I noticed on the keynote, just on that point, I go to a lot of conferences who the Cube does. I'm going to do over 100 events this year. And here is the the the acid test. At the end of the keynotes, the volume of hallway traffic is like swimming up stream. I went to go down to the men's room to do my hair, get my lid straightened up. It was a sea of people. It was a spot. It was a sea of people. And that is a sign that they are staying in the keynotes. Yes, they're on the edge of their seat. They're all smiling. It's like people have a cooling injection of Splunk. It's so excited. And it's unique. This is a cultural thing. It is. How do you guys maintain that post IPO? Because some say, oh, you go public. You got to keep your mouth shut, not say things publicly. But that's not the Splunk way, is it? It's not you know, I'll tell you what the history of this company and it started well before my time, was just a maniacal focus on customer experience and success. And I think that relationship was cemented early on. And all of us that have joined since have really made it a priority to nurture that as much as possible. And we're very proud of that. You heard that this morning with Doug talking about it about, you know, the test dev, right? Free test dev about $5,000 with the free training. And so there's this constant nurturing of your ecosystem to make sure people are up to speed, and they can become more familiar with your products and services. Absolutely. I think it's a big part of why we've been effective. And it's something we pride ourselves in. So what about new products? A lot of new releases announced today on the stage. Several of those certainly play in the era world. And I know that you have a lot to talk about whether you talk about machine learning with your Hadoop data, new setup and everything you've got going on right now. But we announced today Splunk Enterprise and Splunk Cloud 6.5. It's a major new release. And there are really three fundamental areas of advancement. One is around machine learning. We've been actually using machine learning and providing machine learning in our products for a while. But in this release, we're providing what we're calling a machine learning toolkit that enables our customers to do custom analytics based on machine learning to apply to their specific business needs. We've opened it up, leveraging a broad array of open source capabilities for our customers to really do advanced analytics based on machine learning in ways that we feel are going to really hit home for our customers. So I want to ask you on the product side because you had a product management role, now you're in product marketing, which is a little bit more outbound customer facing, but you still have a view into engineering. The product is shifting. It started out, we've been seeing, it's been fun to watch, but now you're at that level now where there's a top line security objective, which has nothing to do with IT. It's just everyone's business agenda at the boardroom level is security. But down in the trenches where you guys are making your bones in the business is IT, IT transformation. Talk about the product roadmap because machine learning and the machine learning toolkit, you becoming an algorithms company, you becoming an enabler still in software, and you guys just had two investments, machine learning investments around threat detection and one around search. Yeah. Does that speak to the product strategy where you guys will fill in the white space with either investments or partnering? And where is the white space vis-a-vis the core product of Splunk? Where's the product going? Great question. I'll try to tackle that. There's a lot of new ones there. Well, our product strategy is really balanced around continue to invest in building a world-class platform. Our largest customer today is has standardized on Splunk and is running multiple petabytes of real-time data in Splunk every day. So this platform notion with advanced analytics to enable a broad array of use cases is fundamental and important to our strategy. But we're also investing in solutions, providing turn key capabilities around security, IT, service intelligence, and in the context of machine learning are investments in machine learning abroad across that portfolio. And so for the solutions, we're delivering turn key machine learning that are very targeted around anomaly detection for IT and user behavior analytics for security in addition to this core platform. Are those pre-packaged solutions or, I mean, the first one, you guys have a platform, so it's breaking down. Platforms and tooling, right? Yes. And then pre-packaged solutions. And pre-packaged solutions on top. That's right. We call them pre-named solutions. And so the customer buys the solutions or the tools and also the license of the platform. So the platform becomes the bread and butter. It's the core engine. It is. It's the foundation that all these use cases and solutions sit on top of. So is the tool kit for machine learning a tool or a solution? It is a tool in the core platform that allows our customers to build custom analytics on their own. But in the context of the solution, we've built a turn key. So it is tailor made to solve a particular problem. So you guys are replicating use cases that you guys have done in the field with customers, packaging them That's right. For easy deployment. That's exactly right. So it's all about time to value. Which everyone wants by they want to go faster. Hurry up. Go faster. All right. Talk about the dynamic between on-prem and cloud because this becomes an industry focus right now. On-prem is a lot of the action and certainly storage. You mentioned some of the storage benefits you're getting with the new solution. But the cloud is an enabler for agility, right? You want to have kind of a mix of hybrid and public. How's that dynamic rationalized out in the product portfolio? One of the things that we've done that I think is quite unique is allow our analytics layer to operate on data irregardless of where it exists. So we have customers that are deploying Splunk on-prem in the cloud in distributed manners with data that's in Splunk or in a data lake. And they have a common interface by which to do the analysis and visualization of their insights. And so the hybrid element is certainly a very important part of value proposition. But we also have customers that really want to build in the cloud. We have a SaaS offering the Splunk cloud. AK cloud native basically, right? Cloud native exactly. And you heard AWS speak earlier this morning about the very strategic nature of our partnership. We run our SaaS service on AWS. And we'll be a reinvent for the folks watching. We'll be there as well with the live coverage. Okay, so from a customer standpoint what's the impact of them? Is it operationally seamless for them on-prem cloud? I mean I got to procure the products, but is there an operational seamlessness that you have there? There is. And they have a choice. You can either run the software yourself and there's some companies that prefer to do that on-prem or in AWS. Or you can just subscribe to our SaaS service and then you don't need to deal with any of the operational aspects of the service. Take a minute to take a minute to share with the audience. What's the new customer environment like now? Because you know the digital transformation has been hyped up till the cows come home these days. But now it's actually happening. People are using Splunk are changing their business models. You know using whether it's prepackaged solutions, which makes a lot of sense. Or using a tool to enable something within their organization. What's the biggest impact this year from your perspective? Looking at the market. That wasn't there last year or that is materialized faster this year from a customer perspective? You know it's remarkable what our customers are able to do because they have access to all this rich data in Splunk. And so I'll give you a few examples. Zillow is able to roll out hundreds of website changes every single day because their development teams are able to track real-time metrics across 2000 data sources in Splunk and do analysis on that. So major business. So they're turning a product their agile and pushing code to the product aka the website in real time based upon data value. That's exactly right because they're able to collect and analyze this data in real time and react quicker. Another great example is NASDAQ. Their online marketing team runs Splunk and they're collecting 10,000 IT and security events every second in order to manage and secure their environments. So we've got customers that are really able to transform their business. We call digital transformation based on the ability to have this access to all this rich data and the ability to do analysis on it in real time. I think that's the poster child in my mind of this modern business using data in real time, impacting the user experience, but open the product. So your customer has a product and the growth for their business is going to come down to how well they can modify that with the data. Exactly. And that is really the holy grail of I mean the security certainly is a holy grail if we can get that solved. But this is actually a business changeover right? It is. This is how businesses are changing. They're using the instrumentation in real time, not waterfall development. The developers are on the front lines. This is an important point and the question is, how does the company do that? Is Splunk a turnkey solution? How do you work with other databases? I mean, you mentioned Hadoop. What if I have Hadoop? How do I fit in there? Well, first I will say that the fact that we're able to collect all this rich data. Real time and do analysis on it from multiple perspectives on the same data is part of what's enabling these companies to actually react and operate in real time in ways that they simply were not able to do with previous technologies. And so that is a fundamental shift. Our view is that your insights are a lot richer when you have access to all the data. And so we enable our customers to use data that's in Splunk real time, but also correlated with structured data stores, data that may be in Hadoop, historical data, and have insight to that hybrid in order to be more informed. Somebody asked a tough question. Here it comes. Fastball. Here comes the heater. How do you talk about data value? Our Wikibon research team is doing a big paper on this right now, because obviously you're pointing out the obvious. Well, to us obvious, but to customers it's now becoming really obvious. Data is really valuable. How do you get that on the balance sheet? Now let's go into the C-level board conversations. You're saying, hey, how do we actually value data? Is it an asset? Do we put it on the balance sheet? Because now you're talking about mechanics and the progression of the business where that tweak of the developer could yield millions in new revenue, change of great value. How do you guys at Splunk talk to customers and how do customers talk back to you around this notion of data value? Are there any parameters? I know it's early days, but what's your thoughts on this? Share your opinion. It's a very good question. We actually have a team that we call them the business value team that actually sit down with customers and look at data sources and help them to project in their world, in their language, based on the nature of their data, the sort of value and returns that they can get. What we see consistently is just about all of our customers start with one problem in mind. But that same data that they may be using for IT troubleshooting has a very direct impact on security and business implications. And as they get this cascading value across a broad range of use cases, that value only escalates. And so this team helps our customers really understand that in their language. Well, just to tease this out, the old paradigm was cost of ownership. Total cost of our TCO. Total cost. That implies you buying an asset and looking at over the life of its value and looking at the cost. Did it, was it good ROI? When you talk about time to value earlier, you talk about data driving a different dynamic. It's revenue. So it's total value potential or it's a whole other paradigm. And, you know, we're looking, people are looking for how to do that. I mean, how do you, how does a customer sit down and saying, I'm impacting the business. I need more cash. I need to buy more stuff. I need to do more. Yes. Because that's the internal dynamic. What's your thoughts on that? Well, I think it's very important. It is, it is a non atypical. So there is an education process that we go through with our customers. I think this business value team is really important in helping in the language of our customers understand what is that value that they're going to get for that initial use case. And then more broadly, as they deploy additional use cases and business oriented value. It's early on right now. No one really has the model. There's no balance sheet item yet. But you could argue, hey, you know, down the road, data on the balance sheet as a lined item. It's a great idea. We're not there yet. You're calling it. Well, that's why we're, well, we are calling this what we're doing a lot of research on this because it's totally unknown. There's no methodology. There's no modeling, but you agree, though, that that value is there. No question about it. Okay. Yeah. So down the road, then. I mean, product development is always about, you know, getting the next greatest thing out there. Yes. I've had great releases, big announcements today. But already, I'm sure there's the conversations are like, where do we go? Now what do we do? So what are you hearing from your customers in terms of what you think you need to be addressing the next big area and how you go about that between now and dot com 2017. It's a great question. We're actually debuting something this this week for the first time, we're introducing Splunk labs that's giving our customers a sneak peek of our future development roadmap ideas. They're not cooked by any means, but the intention is to get feedback, get feedback and have that conversation involving open source integrations and new user experience improvements and a variety of advancements. But that engagement with our customers is really important in our development process. The new tables feature that we introduced and the addup data role and the machine learning toolkit involved close collaboration with early adopters. And those early adopters are speaking on behalf of those features as we launch them today. So very, very important part of that development process is that customer relationship. Talk about the two investments you guys did. Alcalvio advanced threat detection and insight engines was announced to investments. You started investing in the ecosystem. That's very cool. I like that. Don't want the feedback. Great community driven Splunk is but does that fill a white space for you guys? And what are some of the white spaces that you're offering the ecosystem? Because this teaches out a business strategy on the product side. Yes, sounds like you're opening up and saying, Hey, you know, fill in the white spaces, go innovate. Is there any area you can share that you're you're promoting or pointing out to the ecosystem? Yeah, I would say more generally, our new CEO Doug Merritt is is absolutely committed and he hasn't for a while to invest in the ecosystem to really be a data fabric machine data fabric in the way that we are talking about involves requires integration with the broader ecosystem of solutions that our customers are looking for. And so that investment is coming through in partnerships, tight integrations and these investments to really broaden the incremental value that our customers can get by by becoming part of the Splunk family. So thanks for spending the time to coming on the Cuban share and all that insight and sharing the data here inside the cube. Of course, we're like a machine learning algorithm, sharing all the data with you out there. Thanks for watching. We're live here at Orlando Florida's keep up with John Wall. Be right back with more after this short break.